| Base | |
|---|---|
| RHC | 1.16 [1.01, 1.32] |
| Not CHF | 1.71 [1.29, 2.25] |
| Age | 1.03 [1.03, 1.04] |
| Num.Obs. | 5733 |
| AIC | 6882.7 |
| BIC | 7089.0 |
| Log.Lik. | -3410.366 |
| RMSE | 0.45 |
多変量回帰・・・好きですか?
2025-07-12
古くから研究されつくされており、信頼感がある
多くの統計ソフトに入っており、行うのが簡単
解釈性が高く、分かりやすい
本当?
Many regression species
| Base | |
|---|---|
| RHC | 1.16 [1.01, 1.32] |
| Not CHF | 1.71 [1.29, 2.25] |
| Age | 1.03 [1.03, 1.04] |
| Num.Obs. | 5733 |
| AIC | 6882.7 |
| BIC | 7089.0 |
| Log.Lik. | -3410.366 |
| RMSE | 0.45 |
| Base | Interact | |
|---|---|---|
| RHC | 1.16 [1.01, 1.32] | 1.52 [1.02, 2.26] |
| Not CHF | 1.71 [1.29, 2.25] | 1.94 [1.40, 2.69] |
| Age | 1.03 [1.03, 1.04] | 1.03 [1.03, 1.04] |
| RHC:Not CHF | 0.74 [0.49, 1.12] | |
| Num.Obs. | 5733 | 5733 |
| AIC | 6882.7 | 6882.7 |
| BIC | 7089.0 | 7095.7 |
| Log.Lik. | -3410.366 | -3409.366 |
| RMSE | 0.45 | 0.45 |
| Base | Interact | Spline | |
|---|---|---|---|
| RHC | 1.16 [1.01, 1.32] | 1.52 [1.02, 2.26] | |
| Not CHF | 1.71 [1.29, 2.25] | 1.94 [1.40, 2.69] | |
| Age | 1.03 [1.03, 1.04] | 1.03 [1.03, 1.04] | 1.04 [1.03, 1.05] |
| RHC:Not CHF | 0.74 [0.49, 1.12] | ||
| swang1=RHC | 1.49 [1.00, 2.23] | ||
| cat_chf=Others | 1.94 [1.40, 2.70] | ||
| age' | 0.99 [0.96, 1.01] | ||
| age'' | 1.04 [0.89, 1.21] | ||
| swang1=RHC * cat_chf=Others | 0.75 [0.49, 1.14] | ||
| Num.Obs. | 5733 | 5733 | 5733 |
| R2 | 0.140 | ||
| AIC | 6882.7 | 6882.7 | 6884.1 |
| BIC | 7089.0 | 7095.7 | 7110.3 |
| Log.Lik. | -3410.366 | -3409.366 | |
| RMSE | 0.45 | 0.45 |
# A tibble: 5,733 × 6
rowid swang1 estimate conf.low conf.high death_01
<int> <chr> <dbl> <dbl> <dbl> <dbl>
1 1 No RHC 0.606 0.535 0.672 0
2 2 RHC 0.839 0.787 0.880 1
3 3 RHC 0.743 0.675 0.801 0
4 4 No RHC 0.746 0.684 0.800 1
5 5 RHC 0.872 0.830 0.904 1
6 6 No RHC 0.780 0.721 0.829 0
7 7 No RHC 0.585 0.519 0.648 0
8 8 No RHC 0.287 0.231 0.350 1
9 9 No RHC 0.315 0.247 0.394 0
10 10 RHC 0.593 0.535 0.648 0
# ℹ 5,723 more rows
# A tibble: 11,466 × 6
rowid swang1 estimate conf.low conf.high death_01
<int> <chr> <dbl> <dbl> <dbl> <dbl>
1 1 No RHC 0.606 0.535 0.672 0
2 2 No RHC 0.823 0.768 0.868 1
3 3 No RHC 0.721 0.651 0.782 0
4 4 No RHC 0.746 0.684 0.800 1
5 5 No RHC 0.859 0.815 0.893 1
6 6 No RHC 0.780 0.721 0.829 0
7 7 No RHC 0.585 0.519 0.648 0
8 8 No RHC 0.287 0.231 0.350 1
9 9 No RHC 0.315 0.247 0.394 0
10 10 No RHC 0.567 0.508 0.623 0
# ℹ 11,456 more rows
swang1 Estimate Std. Error z Pr(>|z|) S 2.5 % 97.5 %
No RHC 0.638 0.00792 80.5 <0.001 Inf 0.623 0.654
RHC 0.666 0.01034 64.4 <0.001 Inf 0.645 0.686
Type: response
Risk ratio
Estimate Pr(>|z|) S 2.5 % 97.5 %
1.04 0.0433 4.5 1 1.09
Term: swang1
Type: response
Comparison: ln(mean(RHC) / mean(No RHC))
Odds ratio
Estimate Pr(>|z|) S 2.5 % 97.5 %
1.13 0.0454 4.5 1 1.27
Term: swang1
Type: response
Comparison: ln(odds(RHC) / odds(No RHC))
# A tibble: 10,554 × 7
rowid swang1 cat_chf estimate conf.low conf.high death_01
<int> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 1 No RHC Others 0.606 0.535 0.672 0
2 2 No RHC Others 0.823 0.768 0.868 1
3 3 No RHC Others 0.721 0.651 0.782 0
4 4 No RHC Others 0.746 0.684 0.800 1
5 5 No RHC Others 0.859 0.815 0.893 1
6 6 No RHC Others 0.780 0.721 0.829 0
7 7 No RHC Others 0.585 0.519 0.648 0
8 8 No RHC Others 0.287 0.231 0.350 1
9 9 No RHC Others 0.315 0.247 0.394 0
10 10 No RHC Others 0.567 0.508 0.623 0
# ℹ 10,544 more rows
ここから、swang 1の値毎にestimateを平均する
swang1 Estimate Std. Error z Pr(>|z|) S 2.5 % 97.5 %
No RHC 0.562 0.0306 18.3 <0.001 247.4 0.502 0.622
RHC 0.651 0.0317 20.5 <0.001 307.8 0.588 0.713
Type: response
# A tibble: 456 × 7
swang1 cat_chf contrast estimate conf.low conf.high death_01
<chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
1 RHC CHF RHC - No RHC 0.0967 0.000843 0.193 1
2 No RHC CHF RHC - No RHC 0.0904 0.00145 0.179 1
3 No RHC CHF RHC - No RHC 0.0793 0.00122 0.157 0
4 No RHC CHF RHC - No RHC 0.0945 0.000226 0.189 1
5 No RHC CHF RHC - No RHC 0.100 0.00131 0.199 0
6 No RHC CHF RHC - No RHC 0.0998 0.00141 0.198 0
7 No RHC CHF RHC - No RHC 0.0954 0.00136 0.189 1
8 RHC CHF RHC - No RHC 0.0949 0.00119 0.189 0
9 No RHC CHF RHC - No RHC 0.0919 0.00161 0.182 1
10 No RHC CHF RHC - No RHC 0.0816 0.000612 0.163 1
# ℹ 446 more rows
ここから、患者背景がCHFである患者の平均のRisk ratioを計算する
Estimate Pr(>|z|) S 2.5 % 97.5 %
1.16 0.0474 4.4 1 1.34
Term: swang1
Type: response
Comparison: ln(mean(RHC) / mean(No RHC))
A `matchit` object
- method: 1:1 nearest neighbor matching without replacement
- distance: Propensity score
- estimated with logistic regression
- number of obs.: 5733 (original), 4366 (matched)
- target estimand: ATT
- covariates: cat_chf, age, sex, race, edu, income, wtkilo1, temp1, meanbp1, resp1, hrt1, pafi1, paco21, ph1, wblc1, hema1, sod1, pot1, crea1, bili1, alb1, cardiohx, chfhx, immunhx, transhx, amihx
# A tibble: 4,366 × 35
death_yn death_01 death_days swang1 swang_yn cat_chf cat1 age crea1 sex
<dbl> <dbl> <dbl> <chr> <dbl> <chr> <chr> <dbl> <dbl> <chr>
1 0 0 180 No RHC 0 Others COPD 70.3 1.20 Male
2 1 1 45 RHC 1 Others MOSF … 78.2 0.600 Fema…
3 0 0 180 RHC 1 Others MOSF … 46.1 2.60 Fema…
4 1 1 37 No RHC 0 Others ARF 75.3 1.70 Fema…
5 1 1 2 RHC 1 Others MOSF … 67.9 3.60 Male
6 0 0 180 No RHC 0 Others MOSF … 55.0 1 Male
7 1 1 38 No RHC 0 Others ARF 43.6 0.700 Male
8 0 0 180 No RHC 0 Others MOSF … 18.0 1.70 Fema…
9 0 0 180 RHC 1 Others ARF 48.4 0.5 Fema…
10 0 0 180 No RHC 0 Others ARF 34.4 0.5 Male
# ℹ 4,356 more rows
# ℹ 25 more variables: race <chr>, edu <dbl>, income <chr>, wtkilo1 <dbl>,
# temp1 <dbl>, meanbp1 <dbl>, resp1 <dbl>, hrt1 <int>, pafi1 <dbl>,
# paco21 <dbl>, ph1 <dbl>, wblc1 <dbl>, hema1 <dbl>, sod1 <int>, pot1 <dbl>,
# bili1 <dbl>, alb1 <dbl>, cardiohx <int>, chfhx <int>, immunhx <int>,
# transhx <int>, amihx <int>, distance <dbl>, weights <dbl>, subclass <fct>
Estimate Pr(>|z|) S 2.5 % 97.5 %
1.03 0.121 3.0 0.992 1.07
Term: swang1
Type: response
Comparison: ln(mean(RHC) / mean(No RHC))
Estimate Pr(>|z|) S 2.5 % 97.5 %
1.03 0.122 3.0 0.992 1.07
Term: swang1
Type: response
Comparison: ln(mean(RHC) / mean(No RHC))
Estimate Pr(>|z|) S 2.5 % 97.5 %
1.03 0.123 3.0 0.992 1.07
Term: swang1
Type: response
Comparison: ln(mean(RHC) / mean(No RHC))
A weightit object
- method: "glm" (propensity score weighting with GLM)
- number of obs.: 5733
- sampling weights: none
- treatment: 2-category
- estimand: ATE
- covariates: cat_chf, age, sex, race, edu, income, wtkilo1, temp1, meanbp1, resp1, hrt1, pafi1, paco21, ph1, wblc1, hema1, sod1, pot1, crea1, bili1, alb1, cardiohx, chfhx, immunhx, transhx, amihx
# A tibble: 5,733 × 8
death_01 swang_yn age sex race cat_chf crea1 weights
<dbl> <dbl> <dbl> <chr> <chr> <chr> <dbl> <dbl>
1 0 0 70.3 Male white Others 1.20 2.01
2 1 1 78.2 Female white Others 0.600 1.78
3 0 1 46.1 Female white Others 2.60 2.49
4 1 0 75.3 Female white Others 1.70 1.53
5 1 1 67.9 Male white Others 3.60 3.31
6 0 0 86.1 Female white Others 1.40 1.12
7 0 0 55.0 Male white Others 1 1.61
8 1 0 43.6 Male white Others 0.700 1.39
9 0 0 18.0 Female white Others 1.70 1.39
10 0 1 48.4 Female white Others 0.5 2.04
# ℹ 5,723 more rows
Risk ratio and 95% confidence interval
Estimate Pr(>|z|) S 2.5 % 97.5 %
1.05 0.0291 5.1 1 1.1
Term: swang1
Type: probs
Comparison: ln(mean(RHC) / mean(No RHC))
# A tibble: 2 × 2
swang1 mean_death_prob
<chr> <dbl>
1 No RHC 0.642
2 RHC 0.655
すべてのモデルは誤っている。しかし、そのうちのいくつかは役に立つ。